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The concept of a distance, or metric, between the elements of a set is well defined in topology. Let B be any set with x, y, z Є B, and let D be a function from the Cartesian product, B X B, into the set of real numbers, R. D is called a metric on B if the following four statements hold:

1) D(x,y) ≥ 0 for all x, y

2) D(x,y) = D(y,x) for all x, y

3) D(x,y) = 0 if and only if x = yfor all x, y

4) D(x,y) + D(y,z) ≥ D(x,z) for all x, y, z

In this case, the set B having metric D is called a metric space, and is often notated as B, D.

For more information and related definitions, see the links below.

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Q: How do you define a metric space through the use of sets?
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A space is a set with structure. A number of different kinds of mathematical structures (or topologies) exist, including metrics, norms, and inner products. Sets paired with each of these result in a different kinds of spaces, each with a host of interesting properties. Examples of metric spaces include 2-dimensional Euclidean space (as in the surface of a flat sheet of paper), 3-dimensional Euclidean space (a simplification of the world we live in), the Minkowski space (our 3-D world subjected to Einstein's special relativity), and elliptic geometry (which can be used to measure the distances between locations on the surface of the Earth). There also exist topological spaces that are not metric spaces, i.e. spaces that do not have a strict notion of distance between their points. The same set may be paired with different topologies (or different metrics, if applicable), and each of these pairings should be thought of as forming distinct topological (or metric) spaces. There are no spaces that are not sets. On the other hand, any set not paired with a topology is not a space. One can, however, pair any set with the trivial metric d(x,y) = { 0 iff x = y, 1 otherwise } to arrive at a trivial topology. Disregarding this, it is easy to imagine sets that are not spaces, such as for example the set of all automobile models with model year 2013.


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